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Yeah it can be, my teacher mentioned diagrams, but my friend got very good marks without having a diagram. I think what the IBO really demands is having tables and graphs, but I really don't think diagrams are vital. Having said this, I should say that it would be better to follow your teacher's instructions, it wont take long of your time anyways.

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Hi Mahuta. I have one more question. It concerns my graph. I know that for the x-axis, I will put the temperatures I tested, and for the y-axis, it will be how many drops accumulated on the coin before surface tension broke(I'm testing temperature vs. water cohesion). My problem is for each temperature, I did 10 trials. How do I represent this on a graph? Do I have to do 10 seperate graphs? That seems incorrect.

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Hi Mahuta. I have one more question. It concerns my graph. I know that for the x-axis, I will put the temperatures I tested, and for the y-axis, it will be how many drops accumulated on the coin before surface tension broke(I'm testing temperature vs. water cohesion). My problem is for each temperature, I did 10 trials. How do I represent this on a graph? Do I have to do 10 seperate graphs? That seems incorrect.

You can either have multiple graphs, multiple lines on the same graph or take an average of all your results for each temperature and plot those. Ideally, so you can point out odd results and discuss errors etc., you'd do both an average graph AND also multiple graphs/one big graph showing all the other results. Your IA can be as long as you want it to be, remember The whole point of graphs is for data analysis, so you have to show it in whichever way best suits how you want to analyse the data, there's no right and wrong for anything.

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Sandwich is absolutely right in that there are many different ways to go about the data analysis. Here's my take:

If I had these results, I would average the trials and plot the averages on a graph, but if there was one trial that was obviously an outlier, I would discuss that particular trial and attempt to explain the reason behind the outlier, then discount the trial if there was an obvious reason for it being different (such as the method one would use for a titration). By averaging, you are bringing together all your results to get a realistic idea of where the number should be, without plotting too much information on a graph that might overwhelm the reader. Also, this makes it easier to draw a best-fit line if one is required.

If you don't agree with this method or have a better one in mind, there are still lots of different options.